Dynamic Resource Interfaces for Reducing Support Sessions
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Solution Overview
Problem
Existing support systems face inefficiencies due to finite computing and network capacity, leading to user devices queuing for communication sessions, resulting in operational delays and resource waste.
Innovation Solution
Intelligently configured interfaces at user devices provide customized data resources based on historical user behavior and cohort analysis to reduce the need for communication sessions, leveraging machine learning models to predict and proactively offer relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the support system increases computing and network capacity to handle more user devices, then the system can support more simultaneous communication sessions, but the cost and complexity of the system increases
Solution Approach 1:
The system performs preliminary actions by proactively providing relevant information and resources to users before they need to initiate a communication session. This includes predicting user information needs based on historical data and delivering relevant content through the interface, thereby preventing the need for support sessions before they occur.
Solution Approach 2:
The system enables users to serve themselves by providing an interface that automatically delivers relevant information and resources based on user behavior patterns and predictions. Users can access needed information without human agent assistance, reducing the burden on support system capacity while maintaining service quality.
2Reliability
If users wait in a queue for communication sessions, then the support system can manage finite resources, but user experience deteriorates with delays and operational inefficiency increases
Solution Approach 1:
The system anticipates user information needs and delivers relevant content before users would need to queue for support sessions. By analyzing historical user data and predicting future information requirements, the system proactively provides solutions that eliminate the need for users to wait in queues.
Solution Approach 2:
The system introduces an intermediary layer between users and support agents - an intelligent interface that automatically matches users with relevant information and resources. This intermediary handles routine information delivery without requiring human agent involvement, thereby reducing queue wait times while maintaining reliable resource management.
3Ease of operation
If the support system handles all user communication requests, then comprehensive support is provided, but resource waste occurs due to finite capacity and queue management overhead
Solution Approach 1:
The system extracts and handles routine information delivery functions separately from human agent support. By implementing an automated interface that proactively provides relevant information based on user behavior patterns, the system removes low-complexity support tasks from the human agent queue, reducing resource waste while maintaining comprehensive support coverage for more complex issues.
Solution Approach 2:
The system applies different levels of support automation based on user needs and information types. Rather than uniformly handling all requests through human agents or automation, the system dynamically determines the appropriate support level - providing automated information delivery for routine queries while reserving human agent capacity for complex, novel, or high-value support scenarios.
Data Source
AI summary
The disclosed technology relates to providing dynamic interfaces of curated sets of resources for users. The dynamic interfaces can have an effect of reducing a volume of communication sessions initiated with a customer support system. In an example, a resource system associated with data resources (e.g., webpages, documentation) identifies particular data resources that are predicted to be relevant for a given user. The particular data resources are predicted to be relevant for the given user based on the particular data resources being exclusively accessed by historical users who are not active in initiating communication sessions (versus other historical users who are active in initiating communication sessions). Historical users belonging to a same user cohort as the given user are classified as active or non-active in order to identify the particular data resources. The resource system provides a dynamic interface that presents the relevant data resources to the given user.